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Hippocampal assemblies and brain-state-dependent excitatory/inhibitory relationships are revealed using pulsed optogenetic stimulation. 

The incorporation of new information into the hippocampal network is likely to be constrained by its innate architecture and internally generated activity patterns. However, the origin, organization and consequences of such patterns remain poorly understood. In the present study we show that hippocampal network dynamics are affected by sequential neurogenesis. We birthdated CA1 pyramidal neurons with in utero electroporation over 4 embryonic days, encompassing the peak of hippocampal neurogenesis, and compared their functional features in freely moving adult mice. Neurons of the same birthdate displayed distinct connectivity, coactivity across brain states and assembly dynamics. Same-birthdate neurons exhibited overlapping spatial representations, which were maintained across different environments. Overall, the wiring and functional features of CA1 pyramidal neurons reflected a combination of birthdate and the rate of neurogenesis. These observations demonstrate that sequential neurogenesis during embryonic development shapes the preconfigured forms of adult network dynamics. 

Abstract Decades of rodent research have established the role of hippocampal sharp wave ripples (SPW-Rs) in consolidating and guiding experience. More recently, intracranial recordings in humans have suggested their role in episodic and semantic memory. Yet, common standards for recording, detection, and reporting do not exist. Here, we outline the methodological challenges involved in detecting ripple events and offer practical recommendations to improve separation from other high-frequency oscillations. We argue that shared experimental, detection, and reporting standards will provide a solid foundation for future translational discovery. 

The combination of in vivo extracellular recording and genetic-engineering-assisted optical stimulation is a powerful tool for the study of neuronal circuits. Precise analysis of complex neural circuits requires high-density integration of multiple cellular-size light sources and recording electrodes. However, high-density integration inevitably introduces stimulation artifact. We present minimal-stimulation-artifact (miniSTAR) μLED optoelectrodes that enable effective elimination of stimulation artifact. A multi-metal-layer structure with a shielding layer effectively suppresses capacitive coupling of stimulation signals. A heavily boron-doped silicon substrate silences the photovoltaic effect induced from LED illumination. With transient stimulation pulse shaping, we reduced stimulation artifact on miniSTAR μLED optoelectrodes to below 50 μV_pp, much smaller than a typical spike detection threshold, at optical stimulation of >50 mW mm^–2irradiance. We demonstrated high-temporal resolution (<1 ms) opto-electrophysiology without any artifact-induced signal quality degradation during in vivo experiments. MiniSTAR μLED optoelectrodes will facilitate functional mapping of local circuits and discoveries in the brain.

 

Dynamic interactions within and across brain areas underlie behavioral and cognitive functions. To understand the basis of these processes, the activities of distributed local circuits inside the brain of a behaving animal must be synchronously recorded while the inputs to these circuits are precisely manipulated. Even though recent technological advances have enabled such large‐scale recording capabilities, the development of the high‐spatiotemporal‐resolution and large‐scale modulation techniques to accompany those recordings has lagged. A novel neural probe is presented in this work that enables simultaneous electrical monitoring and optogenetic manipulation of deep neuronal circuits at large scales with a high spatiotemporal resolution. The “hectoSTAR” micro‐light‐emitting‐diode (μLED) optoelectrode features 256 recording electrodes and 128 stimulation μLEDs monolithically integrated on the surface of its four 30‐µm thick silicon micro‐needle shanks, covering a large volume with 1.3‐mm × 0.9‐mm cross‐sectional area located as deep as 6 mm inside the brain. The use of this device in behaving mice for dissecting long‐distance network interactions across cortical layers and hippocampal regions is demonstrated. The recording‐and‐stimulation capabilities hectoSTAR μLED optoelectrodes enables will open up new possibilities for the cellular and circuit‐based investigation of brain functions in behaving animals.

 

Gamma oscillations are thought to coordinate the spike timing of functionally specialized neuronal ensembles across brain regions. To test this hypothesis, we optogenetically perturbed gamma spike timing in the rat medial (MEC) and lateral (LEC) entorhinal cortices and found impairments in spatial and object learning tasks, respectively. MEC and LEC were synchronized with the hippocampal dentate gyrus through high- and low-gamma-frequency rhythms, respectively, and engaged either granule cells or mossy cells and CA3 pyramidal cells in a task-dependent manner. Gamma perturbation disrupted the learning-induced assembly organization of target neurons. Our findings imply that pathway-specific gamma oscillations route task-relevant information between distinct neuronal subpopulations in the entorhinal-hippocampal circuit. We hypothesize that interregional gamma-time-scale spike coordination is a mechanism of neuronal communication.

 

The local field potential (LFP) is an aggregate measure of group neuronal activity and is often correlated with the action potentials of single neurons. In recent years, investigators have found that action potential firing rates increase during elevations in power high‐frequency band oscillations (50–200 Hz range). However, action potentials also contribute to theLFPsignal itself, making the spike–LFPrelationship complex. Here, we examine the relationship between spike rates andLFPin varying frequency bands in rat neocortical recordings. We find that 50–180 Hz oscillations correlate most consistently with high firing rates, but that otherLFPbands also carry information relating to spiking, including in some cases anti‐correlations. Relatedly, we find that spiking itself and electromyographic activity contribute toLFPpower in these bands. The relationship between spike rates andLFPpower varies between brain states and between individual cells. Finally, we create an improved oscillation‐based predictor of action potential activity by specifically utilizing information from across the entire recorded frequency spectrum ofLFP. The findings illustrate both caveats and improvements to be taken into account in attempts to infer spiking activity fromLFP.